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Psychophysiological assessment of cognitive and affective responses for prediction of performance in arousal inducing virtual environments

PSYCHOPHYSIOLOGICAL ASSESSMENT OF COGNITIVE AND AFFECTIVE RESPONSES FOR PREDICTION OF PERFORMANCE IN AROUSAL INDUCING VIRTUAL ENVIRONMENTS
by
Christopher Gaelan Courtney
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(PSYCHOLOGY)
December 2012
Copyright 2012 Christopher Gaelan Courtney

The current study sought to examine the psychophysiological response patterns associated with varying levels of threat and cognitive workload in a highly immersive virtual environment (VE) containing a route-learning and navigation task scenario. Participants were led down a specific path through a virtual city by a group of virtual guides. Upon reaching the goal of this initial tour through the city, participants were instructed to navigate back to the starting point of the tour following the same path taken to reach the goal. Two separate experiments were conducted to examine the effects of threat and cognitive workload variations in the environment separately. Psychophysiological responses to threat in Experiment 1 and varying levels of cognitive workload in Experiment 2 were then utilized to develop multiple linear regression (MLR) and artificial neural network (ANN) models for prediction of performance on the navigation task. Comparisons of predictive abilities between the developed models were performed to determine optimal model parameters. Awareness of the navigation task was manipulated such that half of the participants in each experiment were made aware of the navigation task prior to the initial tour to allow for route-learning assessment, while the other half were told only after tour completion to assess response patterns associated with threat and cognitive workload in the absence of the added task of committing the route to memory. Participants made aware of the navigation task evidenced increased efficiency on the return trip through the city. Additionally, the threat level and cognitive workload manipulations were successful in eliciting varying response patterns during areas of high and low intensity stimulus presentations. Finally, ANN models were determined to better predict navigation performance based on psychophysiological responses gleaned during the initial tour through the city. The selected models were able to predict navigation performance with better than 80% accuracy in both Experiments 1 and 2. Applications of the models toward improved human-computer interaction and psychophysiologically-based adaptive systems are discussed.

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PSYCHOPHYSIOLOGICAL ASSESSMENT OF COGNITIVE AND AFFECTIVE RESPONSES FOR PREDICTION OF PERFORMANCE IN AROUSAL INDUCING VIRTUAL ENVIRONMENTS
by
Christopher Gaelan Courtney
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(PSYCHOLOGY)
December 2012
Copyright 2012 Christopher Gaelan Courtney